REVIEW
Cancer Focus
Neutrophil phenotypes and functions in cancer:
A consensus statement
Daniela F. Quail1, Borko Amulic2, Monowar Aziz3, Betsy J. Barnes4,5, Evgeniy Eruslanov6, Zvi G. Fridlender7, Helen S. Goodridge8,
Zvi Granot9, Andre´s Hidalgo10,11, Anna Huttenlocher12,13, Mariana J. Kaplan14, Ilaria Malanchi15, Taha Merghoub16,17,18,19,
Etienne Meylan20,21, Vivek Mittal22,23, Mikael J. Pittet24,25,26,27, Andrea Rubio-Ponce11, Irina A. Udalova28, Timo K. van den Berg29,30,
Denisa D. Wagner31, Ping Wang3, Arturo Zychlinsky32, Karin E. de Visser33,34,37, Mikala Egeblad35,37, and Paul Kubes36,37,38,39
Neutrophils are the first responders to infection and inflammation and are thus a critical component of innate immune
defense. Understanding the behavior of neutrophils as they act within various inflammatory contexts has provided insights into
their role in sterile and infectious diseases; however, the field of neutrophils in cancer is comparatively young. Here, we
summarize key concepts and current knowledge gaps related to the diverse roles of neutrophils throughout cancer
progression. We discuss sources of neutrophil heterogeneity in cancer and provide recommendations on nomenclature for
neutrophil states that are distinct in maturation and activation. We address discrepancies in the literature that highlight a
need for technical standards that ought to be considered between laboratories. Finally, we review emerging questions in
neutrophil biology and innate immunity in cancer. Overall, we emphasize that neutrophils are a more diverse population than
previously appreciated and that their role in cancer may present novel unexplored opportunities to treat cancer.
Introduction
Neutrophils are polymorphonuclear granulocytes of the innate
immune system that are the first line of defense to fight
infection and maintain tissue homeostasis. They differentiate
within the bonemarrow (BM) to yield short-lived cytotoxic cells
whose ebbs and flows in the vasculature and tissues are
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1Rosalind and Morris Goodman Cancer Institute, Department of Physiology, McGill University, Montreal, Quebec, Canada; 2Cellular and Molecular Medicine, University of
Bristol, Bristol, UK; 3Center for Immunology and Inflammation, Feinstein Institutes for Medical Research, Manhasset, NY; 4Center for Autoimmune, Musculoskeletal and
Hematopoietic Diseases, Feinstein Institutes for Medical Research, Manhasset, NY; 5Departments of Molecular Medicine and Pediatrics, Donald and Barbara Zucker School
of Medicine at Hofstra/Northwell, Hempstead, NY; 6Division of Thoracic Surgery, Department of Surgery, Perelman School of Medicine at the University of Pennsylvania,
Philadelphia, PA; 7Hadassah Medical Center, Institute of Pulmonary Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; 8Board of Governors
Regenerative Medicine Institute and Research Division of Immunology, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA; 9Department of
Developmental Biology and Cancer Research, Hebrew University of Jerusalem, Jerusalem, Israel; 10Vascular Biology and Therapeutics Program and Department of
Immunobiology, Yale University School of Medicine, New Haven, CT; 11Area of Cell and Developmental Biology, Centro Nacional de Investigaciones Cardiovasculares Carlos
III, Madrid, Spain; 12Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI; 13Department of Pediatrics, University of
Wisconsin-Madison, Madison, WI; 14Systemic Autoimmunity Branch, Intramural Research Program, National Institute of Arthritis and Musculoskeletal and Skin Diseases,
National Institutes of Health, Bethesda, MD; 15Tumour-Host Interaction Laboratory, The Francis Crick Institute, London, UK; 16Ludwig Collaborative and Swim Across
America Laboratory, Memorial Sloan Kettering Cancer Center, New York, NY; 17Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New
York, NY; 18Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY; 19Weill Cornell Medical College, New York, NY; 20Lung Cancer and
Immuno-Oncology Laboratory, Bordet Cancer Research Laboratories, Institut Jules Bordet, Universite´ Libre de Bruxelles, Anderlecht, Belgium; 21Laboratory of
Immunobiology, Universite´ Libre de Bruxelles, Gosselies, Belgium; 22Department of Cardiothoracic Surgery, Neuberger Berman Foundation Lung Cancer Research Center,
Weill Cornell Medicine, New York, NY; 23Department of Cell and Developmental Biology, Weill Cornell Medicine, New York, NY; 24Department of Pathology and
Immunology, University of Geneva, Geneva, Switzerland; 25Ludwig Institute for Cancer Research, Lausanne Branch, Lausanne, Switzerland; 26Department of Oncology,
Geneva University Hospitals, Geneva, Switzerland; 27AGORA Cancer Research Center, Lausanne, Switzerland; 28University of Oxford, Kennedy Institute of Rheumatology,
Oxford, UK; 29Laboratory of Immunotherapy, Sanquin Research, Amsterdam, Netherlands; 30Department of Molecular Cell Biology and Immunology, Amsterdam
University Medical Center, Amsterdam, Netherlands; 31Program in Cellular and Molecular Medicine, Division of Hematology/Oncology, Boston Children’s Hospital and
Harvard Medical School, Boston, MA; 32Department of Cellular Microbiology, Max Planck Institute for Infection Biology, Berlin, Germany; 33Division of Tumour Biology and
Immunology, Oncode Institute, Netherlands Cancer Institute, Amsterdam, Netherlands; 34Department of Immunohematology and Blood Transfusion, Leiden University
Medical Centre, Leiden, Netherlands; 35Cold Spring Harbor Laboratory, Cold Spring Harbor, NY; 36Department of Pharmacology and Physiology, Cumming School of
Medicine, University of Calgary, Calgary, Alberta, Canada; 37Banbury Center meeting organizers, Diverse Functions of Neutrophils in Cancer, Cold Spring Harbor Laboratory,
New York, NY; 38Department of Microbiology, Immunology & Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; 39Calvin,
Phoebe and Joan Snyder Institute for Chronic Diseases, University of Calgary, Calgary, Alberta, Canada.
Correspondence to Daniela F. Quail: daniela.quail@mcgill.ca
T.K. van den Berg’s present address is Byondis BV, Nijmegen, Netherlands. K.E. de Visser, M. Egeblad, and P. Kubes were meeting organizers.
© 2022 Quail et al. This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).
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diurnally regulated. Neutrophils are highly abundant in circu-
lation, accounting for up to ∼70% of all peripheral leukocytes in
humans and ∼10–20% in mice (Mestas and Hughes, 2004).
Rough estimates suggest humans produce ∼1 billion neutrophils
daily per kilogram of body weight at steady state, and this may
extend to 10 billion under inflammatory conditions (Ley et al.,
2018). Neutrophils contain granules with an arsenal of cytotoxic
factors, such as antimicrobial compounds, serine proteases, ly-
sozyme, defensins, metalloproteases, and enzymes that mediate
oxidative burst (Amulic et al., 2012). Their principal innate
functions include degranulation, phagocytosis, and release of
neutrophil extracellular traps (NETs; expelled DNA webs deco-
rated with microbicidal proteins such as myeloperoxidase,
elastase, and defensins). In addition, emerging studies indicate
that some neutrophils can present antigens, co-regulate T cell
responses, and kill in an antibody-dependent manner (Mantovani
et al., 2011; Matlung et al., 2018). Usually, neutrophil cytotox-
icity is beneficial and necessary to fight off infection; however,
under chronic conditions, it can cause collateral tissue
damage, particularly within highly vascularized tissues
(Adrover et al., 2020; Adrover et al., 2019; Blanco et al., 2021;
Clark et al., 2007).
Neutrophils are recruited to sites of sterile injury in large
numbers, challenging the notion that these cells are exclusively
antimicrobial and raising the possibility that they actively or-
chestrate tissue repair (Peiseler and Kubes, 2019; Phillipson and
Kubes, 2011). This includes cancer, where various pro-tumorigenic
functions of neutrophils have been described. Notably, neu-
trophils promote almost every aspect of cancer progression,
such as primary tumor growth and metastasis (Coffelt et al.,
2015; Cools-Lartigue et al., 2013; Demers et al., 2016; El Rayes
et al., 2015; Engblom et al., 2017; Gershkovitz et al., 2018a;
Park et al., 2016; Quail et al., 2017; Yang et al., 2020), cancer
stem cell maintenance (Wculek and Malanchi, 2015), exit
from dormancy and cell cycle progression (Albrengues et al.,
2018; Houghton et al., 2010; Szczerba et al., 2019), impaired
immunosurveillance (Casbon et al., 2015; Shaul et al., 2021;
Spiegel et al., 2016; Veglia et al., 2019; Yajuk et al., 2021), and
therapeutic resistance (Salvagno et al., 2019; Siwicki et al.,
2021; Wisdom et al., 2019). Nevertheless, other studies have
found that neutrophils can have an anti-tumorigenic role,
including cytotoxicity against tumor cells (Bouti et al., 2021;
Cui et al., 2021; Gershkovitz et al., 2018a; Gershkovitz et al.,
2018b; Hirschhorn-Cymerman et al., 2020; Martinez Sanz
et al., 2021; Martı´nez-Sanz et al., 2021; Matlung et al., 2018)
and enhanced tumor cell clearance (Blaisdell et al., 2015;
Eruslanov et al., 2014; Singhal et al., 2016), particularly in
early-stage disease. Given the discordant mechanisms by
which neutrophils can influence cancer, it is apparent that we
lack a fundamental understanding of how neutrophil biology
shifts in the context of malignancy.
This consensus statement follows a meeting at the Banbury
Center at Cold Spring Harbor Laboratory focused on new and
emerging concepts in the field of neutrophils in cancer. Here we
summarize and expand on those discussions by reviewing cur-
rent literature on neutrophil heterogeneity, discrepancies in the
field, and open questions requiring further investigation.
The unheeded complexity of neutrophil heterogeneity
in cancer
Classical views of neutrophils in cancer have adopted a binary
classification system that compartmentalizes neutrophils as ei-
ther pro- or anti-tumorigenic. For many years, this has served as
a satisfactory working hypothesis; however, with emerging re-
search, it is clear that this polarized paradigm is inadequate.
Akin to our evolving understanding of macrophage diversity
(Ginhoux et al., 2016), recent research has identified diverse
neutrophil states with widespread functionality. The effects of
neutrophils on tumor biology have been covered by several
excellent reviews (Coffelt et al., 2016; Engblom et al., 2016; Giese
et al., 2019; Granot, 2019; Hedrick and Malanchi, 2022; Jaillon
et al., 2020; Nicolas-Avila et al., 2017; Shaul and Fridlender,
2019). Therefore, we focus our discussion on the reciprocal ef-
fect, i.e., how the tumor and host environments regulate neu-
trophil heterogeneity (quantity and quality) to yield highly
diverse cellular states with broad functionality.
Neutrophil phenotypes driven by the tumor
Tumor regulation of neutrophil quantity. Tumor-induced
neutrophilia requires signals to expand neutrophil progenitor
pools and mediate chemotaxis. Two CSFs critical for granulo-
poiesis are granulocyte (G)-CSF (CSF-3) and GM-CSF (CSF-2;
Hamilton and Achuthan, 2013). Early studies identified that
highly metastatic tumors were capable of secreting G-CSF to
stimulate the accumulation of neutrophils to promotemetastasis
(Kowanetz et al., 2010). The effect of tumor- or stroma-derived
G-CSF on Ly6G+ or Gr1+/hi granulocytes has since been con-
firmed by many additional groups (Casbon et al., 2015; Coffelt
et al., 2015; Hsu et al., 2019; Strauss et al., 2015; Wculek and
Malanchi, 2015; Welte et al., 2016), and it is now known that
mechanistically, tumor-derived G-CSF skews hematopoiesis
within BM toward the myeloid lineage resulting in elevated
systemic frequencies of both immature and mature neutrophils
with immunosuppressive properties in mice (Casbon et al.,
2015). G-CSF production by tumors can be regulated upstream
by IL-23 and IL-17 supplied by phagocytes and T cells, respec-
tively (Coffelt et al., 2015; Smith et al., 2007; Stark et al., 2005).
Additional studies have suggested a similar role for tumor- or
stroma-derived GM-CSF in promoting the expansion of neu-
trophils and their progenitors in association with cancer pro-
gression (Bayne et al., 2012; Bronte et al., 1999; Bronte et al.,
2003; Kohanbash et al., 2013; Wu et al., 2014). The central role
of these CSFs in tumor-associated inflammation mirrors that of
emergency granulopoiesis, a survival mechanism to systemically
control disseminated infections when the immune system be-
comes maximally challenged (Manz and Boettcher, 2014). As
such, questions have emerged over the use of G/GM-CSF in
cancer patients following chemotherapy-induced myelosup-
pression. This is now being explored in retrospective studies, in
which, fortunately, G-CSF does not appear to exacerbate brain
metastasis in patients with de novo stage IV breast cancer (Fujii
et al., 2021); however, these analyses need to be expanded to
additional cancer contexts.
Activation of the chemokine receptor CXCR2 is a key event
for neutrophil mobilization from BM (Ley et al., 2018), whereas
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BM retention is regulated by CXCR4 (Adrover et al., 2019; Eash
et al., 2010; Martin et al., 2003). The coordination of CXCR2 and
CXCR4 is regulated diurnally and underlies circadian pattern of
neutrophil flux in steady state (Adrover et al., 2019; Casanova-
Acebes et al., 2013). In human cancer, the CXCR2 ligand CXCL8
(IL-8) is abundantly secreted by various tumor types
(Sanmamed et al., 2014) and is sufficient to regulate neutrophil
recruitment and NETosis (Alfaro et al., 2016; Nie et al., 2019).
Consistently, CXCR2 inhibitors can reduce tumor-associated
NETs in models of melanoma, breast cancer, and colorectal
cancer (Park et al., 2016; Park et al., 2015; Teijeira et al., 2020).
Neutrophil CXCR2 signaling has been linked to adaptive im-
mune responses by CD8+ T cells, and there is interest in com-
bining CXCR2 inhibitors with immunotherapy. For example, in
models of colitis-induced tumorigenesis, CXCR2 signaling
within Ly6G+ myeloid cells suppresses tumoricidal functions of
CD8+ T cells, as assessed by CD107a, IFNɣ, Prf1, and Gzmb
(Katoh et al., 2013). In murine oral, renal, and pancreatic tumor
models, CXCR2 inhibition results in neutrophil depletion co-
inciding with increased survival, T cell infiltration, and im-
munotherapy response (Chao et al., 2016; Najjar et al., 2017;
Steele et al., 2016; Sun et al., 2019). In preclinical models of
childhood cancers such as rhabdomyosarcoma, CXCR2+Ly6G+
cells mediate local immunosuppression, while CXCR2 inhibi-
tion improves immune checkpoint blockade efficacy (Highfill
et al., 2014). Similarly, retrospective studies have shown that
serum IL-8 is an independent biomarker of reduced efficacy of
immune checkpoint inhibitors in patients, and coincides with
increased neutrophils within tumors (Schalper et al., 2020; Yuen
et al., 2020). Preclinical studies have implicated other CXCR2
ligands in neutrophil recruitment to tumors (Liu et al., 2016), and
it is possible that these may serve as additional biomarkers in
patients. In the era of cancer immunotherapy, these findings
highlight the importance of understanding neutrophil dynamics
as they relate to anti-tumor T cell responses.
In addition to specific tumor-supplied factors, genetic events
within cancer cells underlie a broader shift in the tumor se-
cretory profile with compounded effects onmicroenvironmental
composition (Duits and de Visser, 2021). One such event is Tp53
loss, which has pronounced effects on the tumor myeloid land-
scape. In breast cancer, loss of Tp53 upregulates the secretion of
WNT ligands, which stimulate macrophages to produce IL-1β,
mediate neutrophilic inflammation, and potentiate metastatic
progression (Wellenstein et al., 2019). In lung cancer, Tp53 loss
and Kras activation lead to elevated levels of the receptor for
advanced glycation end products (RAGE) within blood, which
educates distant osteoblasts to stimulate the expansion of long-
lived pro-tumorigenic SiglecFhi neutrophils (in contrast,
SiglecFlo neutrophils are enriched in healthy lung; Engblom et al.,
2017; Pfirschke et al., 2020). In Kras-driven pancreatic can-
cer, loss of Tp53 stimulates the production of myeloid chemokines,
including CXCR2/3 ligands, resulting in the recruitment of
immunosuppressive CD11b+ myeloid cells (Blagih et al., 2020). In
prostate cancer, the combination of Pten and Tp53 loss enhances
CXCL17 secretion and recruitment of CD11b+Gr1+ immunosup-
pressive neutrophils (Bezzi et al., 2018). Combined loss of Pten
and Tp53 is also linked to CD11b+Gr1+ myeloid cell accumulation
in breast cancer models (Welte et al., 2016). These studies
demonstrate that loss of Tp53 in cancer cells, either alone or
combined with additional genetic events, leads to an infiltrative
myeloid microenvironment coinciding with tumor progression.
Other genetic driver mutations might influence the neutrophilic
immune landscape, such as oncogenic Kras mutations that en-
hance IL-8 production (Hamarsheh et al., 2020; Sparmann and
Bar-Sagi, 2004). However, in comparing each study, neutrophil
phenotypes were highly diverse, underscoring the regulatory
relationship between tumor genotypes and neutrophil states in
cancer.
Tumor regulation of neutrophil quality. One of the first pre-
clinical studies to discriminate between neutrophil states in
cancer described N1/anti-tumorigenic and N2/pro-tumorigenic
neutrophils within tumors, whereby transition to N2 was reg-
ulated by TGF-β (Fridlender et al., 2009). TGF-β acts in part
through its ability to regulate pro-inflammatory cytokines and
neutrophil chemoattractants, such as CXCR2 ligands CXCL1/2/5
(Fridlender et al., 2009; Haider et al., 2019; Yang et al., 2008),
and may even synergize with CSFs in BM (Celada and Maki,
1992; Hestdal et al., 1993; Keller et al., 1991). Although TGF-β
can be supplied by the tumor itself, it can also be derived from
microenvironmental sources, including myeloid cells (Yang
et al., 2008). Subsequent studies ascribed the terms high-
density neutrophils (also known as “normal density”) or low-
density neutrophils to anti/pro-tumoral subsets, based on
buoyant density, granularity, and maturation state (Hsu et al.,
2019; Sagiv et al., 2015). These density fractions were first de-
scribed in early work in autoimmunity (Hacbarth and Kajdacsy-
Balla, 1986; Pember et al., 1983; Pember and Kinkade, 1983) and
later refined using mass cytometry (cytometry time of flight
[CyTOF]) to identify subpopulations within each fraction asso-
ciated with cancer outcomes (Shaul et al., 2020; Zhu et al.,
2020). Like N2 neutrophils, the low-density neutrophil subset
is driven by TGF-β and exhibits immunosuppressive properties
in cancer (Sagiv et al., 2015), and is associated with advanced
disease (Brandau et al., 2011; Schmielau and Finn, 2001; Shaul
et al., 2020). These early discoveries were among the first to
challenge our understanding of neutrophil plasticity and het-
erogeneity in cancer.
Since then, many studies have identified unique neutrophil
phenotypes in cancer. Single-cell RNA sequencing (RNA-seq) of
patient lung tumors identified five neutrophil clusters that only
partially overlap with those in blood (Zilionis et al., 2019). Of
these, three clusters are conserved in mice, including one that is
uniquely found in tumors and not healthy tissue, with high
levels of Ctsb and Ccl3 (termed N5; see Fig. 2 A; Siwicki and Pittet,
2021; Zilionis et al., 2019). Similar observations were made with
CyTOF on blood samples from melanoma and lung cancer pa-
tients (Shaul et al., 2020; Zhu et al., 2020), where at least five
neutrophil states were identified (Zhu et al., 2020). Specific
neutrophil states are associated with patient outcomes (Zhu
et al., 2020; Zilionis et al., 2019); for example, N5 neutrophils
(detected by immunostaining for peptidase inhibitor 3) are as-
sociated with tumor growth and worse prognosis in lung cancer
patients (Zilionis et al., 2019), and partially resemble pro-
tumorigenic SiglecFhi neutrophils in mice (Engblom et al.,
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2017). Moreover, distinct functional proficiencies can be as-
cribed to each state, including differential capacities for
phagocytosis and ROS production (Zhu et al., 2020). However,
studies exhaustively testing additional functions, such as
NETosis, have been limited, as most research is focused on the
bulk analysis of neutrophils. As single-cell technologies have
gained considerable momentum in recent years, expanding our
mechanistic understanding of how distinct neutrophil states
may yield unique effects in cancer immunology will be im-
portant for developing neutrophil-targeted immunotherapies.
Moreover, it will be critical to understand the contribution of
distinct neutrophil states to immunotherapy-related adverse
events (Siwicki et al., 2021), which often necessitate discon-
tinuation of these therapies.
ROS production by neutrophils has several functional con-
sequences, one of which is NETosis. In laboratory models,
neutrophils from mice with leukemia, breast cancer, or lung
cancer are prone to NETosis compared with those from healthy
mice (Demers et al., 2012). Similar observations have been re-
ported in humans; in esophageal, gastric, and lung cancer pa-
tients, NETs are elevated in blood compared with healthy
individuals (Rayes et al., 2019). Although these observations are
associative, emerging work is now addressing the possibility
that tumors play a causative role in NETosis. Moreover, it is
becoming clear that NETs that form in response to malignancy
have multifaceted effects. Early studies have shown that cancer-
induced NETs act largely within the circulation, where they
facilitate cancer-associated thrombosis (Demers et al., 2012; Hell
et al., 2016; Thalin et al., 2016; Thomas et al., 2015) and sequester
circulating tumor cells to escort metastases (Cools-Lartigue
et al., 2013). Subsequent studies revealed that NETs affect es-
sentially every step of the metastatic cascade, including primary
tumor progression (Guglietta et al., 2016), invasion and migra-
tion (Park et al., 2016), survival in the circulation (Spiegel et al.,
2016; Szczerba et al., 2019; Teijeira et al., 2020), chemotaxis to
secondary niches (Yang et al., 2020), extravasation (McDowell
et al., 2021; Spiegel et al., 2016), metastatic colonization (Wculek
and Malanchi, 2015; Yang et al., 2020), and outgrowth of met-
astatic tumor cells (Albrengues et al., 2018; Xiao et al., 2021).
However, a remaining knowledge gap is how tumors trigger
NETosis—Is this a direct consequence of tumor-derived factors?
Is it a systemic response to cancer-associated inflammation? Or
is it a broader shift in neutrophil developmental and aging
programs? Co-culture experiments with tumor cells and NE-
Tosing neutrophils have hinted toward tumor-supplied factors,
such as G-CSF, IL-8, or cathepsin C (Alfaro et al., 2016; Demers
et al., 2012; Demers et al., 2016; Park et al., 2016; Xiao et al.,
2021), but deeper mechanistic insights are needed to dissect
contributions from developmental and diurnal neutrophil states.
To date, there are no clinical trials testing NET inhibitors in cancer
patients; however, clinical trials with recombinant human DNase1
are being conducted in patients with COVID-19 (NCT04409925,
NCT04359654, NCT04445285, NCT04541979, NCT04432987, and
NCT04402944), which will provide a foundation for translating
NET-targeted therapies to immuno-oncology.
Neutrophils can adopt immunosuppressive functions both
systemically and within the tumor microenvironment. This is
partially due to metabolic reprogramming of neutrophils in the
context of cancer, where nutrient sharing between cells and
tissues becomes subverted to accommodate the high energy
demands of a rapidly growing tumor. The prevailing dogma is
that neutrophils are almost exclusively glycolytic, and while this
is true in some cancer settings (Ancey et al., 2021; Patel et al.,
2018), it is not always the case. In the 4T1 transplantable
mammary tumor model, the glucose-restricted microenviron-
ment causes neutrophils to utilize mitochondrial fatty acid ox-
idation, leading to enhanced ROS production, T cell suppression,
NETosis, and liver metastasis (Hsu et al., 2019; Rice et al., 2018).
Moreover, in the spontaneous MMTV-PyMT breast cancer
model, neutrophils secrete leukotrienes, which are lipid prod-
ucts of Alox5-mediated oxidation of arachidonic acid, to promote
tumor survival and colonization within the pre-metastatic niche
(Wculek and Malanchi, 2015). Changes in lipid metabolism in
neutrophils have also been observed in mouse models of lung
cancer, colon cancer, and rhabdomyosarcoma (Al-Khami et al.,
2017; Hossain et al., 2015; Kaczanowska et al., 2021; Tavazoie
et al., 2018), and in patients in association with immunosup-
pression (Condamine et al., 2016). Lipid uptake by neutrophils
has been reported in several cancer models via fatty acid
transport protein 2 (FATP2) or adipose triglyceride lipase (Li
et al., 2020b; Veglia et al., 2019), which not only causes immu-
nosuppression of antigen-specific CD8+ T cells (Veglia et al.,
2019), but also creates an energy reservoir for metastasizing
cells (Li et al., 2020b). Lipid uptake can also be regulated by
tumor-derived G/GM-CSF (Al-Khami et al., 2017). Elegant
models using a cell-penetrant fluorescent labeling system to
study cellular neighbors of metastatic breast cancer cells in the
lung microenvironment have shown that neutrophils within the
immediate niche of the tumor exhibit elevated oxidative phos-
phorylation and ROS production (Ombrato et al., 2019), although
immunosuppressive functions in this context have not been
evaluated. Of note, the immunosuppressive consequences of low
glucose levels in the tumor microenvironment are not restricted
to granulocytes and may extend to regulatory T cells, dendritic
cells, and M2-like macrophages (Angelin et al., 2017; Cubillos-
Ruiz et al., 2015; Vats et al., 2006; Vitale et al., 2019; Wang et al.,
2020a; Watson et al., 2021).
Neutrophil phenotypes driven by the host environment
Physiologic states that influence neutrophil biology. Neutrophil
biology is strongly influenced by variables in host physiology,
such as sex, age, circadian rhythms, and anatomical location
(Fig. 1). For example, peripheral neutrophils with an immature
phenotype are elevated in young men compared with young
women and exhibit increased mitochondrial metabolism
(Blazkova et al., 2017; Gupta et al., 2020). In contrast, women
have more mature neutrophils with a heightened capacity for
activation, including hyperresponsiveness to type I IFNs and
enhanced capacity for NETosis (Blazkova et al., 2017; Gupta
et al., 2020). Of note, ex vivo NETosis assays with mouse neu-
trophils have reported the opposite effect (Lu et al., 2021). Ad-
ditionally, neutrophil phenotypes are not static; sex dimorphism
is lost with aging, and in females, the immature neutrophil
phenotype is enhanced during pregnancy as estrogen levels rise
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(Blazkova et al., 2017; Lu et al., 2021). Interestingly, estrogen
signaling can promote intratumoral immunosuppressive activity
of estrogen receptor (ER)–positive Ly6CloLy6G+myeloid cells and
enhance cancer progression inmice, even in ER-negative tumors
(Svoronos et al., 2017). At the molecular level, multi-omics
analyses of male versus female BM neutrophils in mice have
confirmed sex dimorphic differences: transcriptomics revealed a
female bias for extracellular matrix and cell surface–related
pathways and a male bias for chromatin and cell cycle–related
pathways; metabolomics showed differences in nucleotide and
amino acid metabolism; and lipidomics showed a male bias for
increased lipid storage (Lu et al., 2021). These fundamental dif-
ferences are likely to mechanistically underlie sex dimorphic
functional variations observed in steady-state, autoimmunity, and
infection (Klein and Flanagan, 2016; Kourtis et al., 2014); however,
the impact on tumor biology remains unexplored.
Although neutrophils are highly sex dimorphic throughout
life, the effects of aging on neutrophils appear to be similar,
regardless of sex (Lu et al., 2021). Aging is associated with
chronic, low-grade inflammation leading to a gradual decline in
immune function over time, which likely underlies the higher
incidence of infection, autoimmunity, and cancer in the elderly.
In mouse models, hematopoietic stem cells (HSCs) in BM are
skewed toward myeloid lineage specification both in steady-
state and following transplantation of aged HSCs into young
mice (Rossi et al., 2005), suggesting that the age-related myeloid
bias is cell intrinsic. Similar observations have been made in
humans by comparing elderly (65–85 yr) and young (20–31 yr)
individuals (Pang et al., 2011). In mice, analysis of male and fe-
male BM neutrophils from young (4–5 mo) and old (20–21 mo)
mice has shown that aging is associated with significant changes
to neutrophil gene expression, with relatively minimal changes
to metabolomic or lipidomic profiles (Lu et al., 2021). Aging
downregulates pathways related to chromatin organization,
despite no functional differences in cell-cycle phase distribution,
suggesting possible relevance to NETosis. Pathways related to
autophagy, which are critical for normal neutrophil differenti-
ation and function (Riffelmacher et al., 2017), are also upregu-
lated with aging (Lopez-Otin et al., 2013; Lu et al., 2021). Within
some lymphoid organs, including BM, LNs, and spleen, neutro-
phil frequencies increase in aged mice (22–24 mo; equivalent to
60–70 human yr) compared to young mice (2–3 mo; equivalent
to 18 human yr), yet become functionally dysregulated (e.g.,
display reduced phagocytosis, increased senescence, and dys-
regulated NETosis; Hazeldine et al., 2014; Lu et al., 2021; Tomay
et al., 2018; Wenisch et al., 2000). It remains unclear how
phenotypes reported in young mice (which are typically used in
cancer research) compare with those in aged mice where neu-
trophil function may be intrinsically different. It is possible that
this variable contributes to the differences observed between
neutrophils in mouse models and humans (discussed in Neu-
trophils with an anti-tumorigenic…; Eruslanov et al., 2017).
In both males and females, neutrophils are replenished di-
urnally, and the circadian regulation of neutrophil aging trans-
lates to distinct phenotypes at different times of the day
(Adrover et al., 2019; Casanova-Acebes et al., 2018; Casanova-
Acebes et al., 2013). In mice, neutrophils newly released into the
circulation (“fresh” neutrophils) exhibit enhanced migratory
programs including an enhanced capacity for vascular rolling,
adhesion, and extravasation into inflamed tissues, whereas neu-
trophils toward the end of their lifecycle (“aged” neutrophils)
show enhanced antimicrobial activity and can be retained
within healthy tissues during periods of organismal activity
(note that for mice, the active period is at night; Adrover
et al., 2019; Zhang et al., 2015). In steady-state, circulating
neutrophils “disarm” their cytotoxic functions as they age by
progressively degranulating; this phenomenon likely makes
them less harmful once they reach tissues and may help offset
potential collateral damage to highly vascularized niches, in-
cluding lung (Adrover et al., 2020). These changes are dependent
on CXCR2 (Adrover et al., 2020), which, in addition to its
functions above, is a master regulator of neutrophil diurnal ac-
tivation (Adrover et al., 2019). A functional consequence of these
time-dependent properties is that metastatic events may be di-
urnally regulated. Elegant circadian experiments have shown
that B16F1 melanoma cells injected intravenously into syngeneic
mice in the morning form overt lung metastases while injections
in the evening yield minimal metastatic disease, and this dif-
ference is mitigated when neutrophils are depleted (Casanova-
Acebes et al., 2018). These findings raise the possibility that the
efficacy of neutrophil-targeted therapies may be different de-
pending on the time of administration, and may even extend to
other therapies that are influenced by neutrophil function. This
concept was recently explored in the context of immune
checkpoint blockade in melanoma patients, where it was sug-
gested that daytime infusions may be more effective than
evening infusions (Qian et al., 2021).
Neutrophil aging is regulated in part by intrinsic factors,
such as the molecular clock transcription factor Bmal1 (Adrover
et al., 2019), and also extrinsic factors, such as the microbiome,
which neutrophils can sense through signaling from their pat-
tern recognition receptors (Zhang et al., 2015). The microbiome
regulates neutrophil differentiation and function during infec-
tion (Balmer et al., 2014; Clarke et al., 2010; Deshmukh et al.,
2014; Khosravi et al., 2014). Germ-free and antibiotic-treated
mice have reduced frequencies of circulating aged neutrophils,
whereas this phenomenon is reversed by fecal transplantation
or LPS administration (Zhang et al., 2015). These studies suggest
that dysbiosis, obesity, antibiotic use, or other factors that
modify the microbiome may alter neutrophil activity both in
steady-state and in response to inflammatory stimuli, including
cancer. A role for the gut microbiome in regulating cancer
progression and response to immunotherapy is also emerging in
humans (Gopalakrishnan et al., 2018; Helmink et al., 2019;
Matson et al., 2018; Routy et al., 2018). For instance, two-phase
I/II clinical trials found that fecal microbiota transplantation can
sensitize previously refractory cancer patients to immune
checkpoint inhibitors (Baruch et al., 2021; Davar et al., 2021).
These responses were associated with improved T cell infiltra-
tion and activation within tumors, and it is likely that innate
immune components, including neutrophils, are also involved,
given their ability to directly sense bacteria.
Neutrophils patrol healthy tissues in steady-state, and there
is tissue specificity to the dynamics of neutrophil infiltration and
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phenotype. At homeostatic baseline, neutrophils are abundant in
BM, spleen, and lung, and with lower frequencies in liver, in-
testine, muscle, skin, andwhite adipose tissue (Casanova-Acebes
et al., 2018). Studies have also identified neutrophils that re-
circulate through LNs where they protect against infection
within the lymphatics (Bogoslowski et al., 2020). Parabiosis
experiments with CD45.1 and CD45.2 mice showed that blood-
derived neutrophils accumulate and are retained in most tissues
in the evening, whereas the intestine and liver show minimal
rhythmicity (Casanova-Acebes et al., 2018). Neutrophil spatial
patterning is also tissue specific, where distribution within tis-
sues appears to be somewhat random in most organs, whereas
the intestine and spleen exhibit a more purposeful localization
pattern (Casanova-Acebes et al., 2018; Puga et al., 2011).
Functionally, neutrophil half-life is dramatically distinct be-
tween tissues; the total lifespan ranges from 28.9 h in liver (8.7 h
half-life) to 67.1 h in BM (20.2 h half-life), with blood, spleen,
lung, intestine, and skin ranging in between (Ballesteros et al.,
2020). Similarly in humans, a lifespan of up to 5.4 d has been
reported (Pillay et al., 2010), though this remains controversial
(Tofts et al., 2011). Moreover, tissue-specific analyses of RNA,
protein, and chromatin have revealed striking heterogeneity
between mouse neutrophils from distinct anatomical sites, in-
cluding BM, lung, intestine, skin, spleen, and blood (Ballesteros
et al., 2020; Xie et al., 2020). Together these findings strongly
challenge the prevailing dogma that neutrophils are functionally
uniform cells with rapid turnover. Despite neutrophils being the
most abundant myeloid cell type in the body, a comparison of
Figure 1. Physiologic and pathologic states that influence neutrophil heterogeneity in cancer. Tumor-derived factors (e.g., G-CSF, GM-CSF, CXCR2
ligands, TGF-β) and tumor genetics (e.g., Tp53 loss, oncogenic Kras) regulate neutrophil recruitment and activation states in cancer. This is compounded by
physiologic (e.g., age, sex, time, tissue, microbes) and pathologic (e.g., obesity, infection, cigarette smoke) states of the host that differentially prime neutrophils
to respond to tumor-derived cues. Each of these factors culminate to yield a myriad of different neutrophils “flavors” in cancer that regulate essentially all steps
of disease progression, from the primary site to the metastatic niche. Created with BioRender.com.
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how tissue-specific properties of neutrophils might differen-
tially impact cancers arising in different organs has not been
explored.
Pathologic states that influence neutrophil biology. Pathologic
conditions add further complexity to the influence of host
physiology on immune function (Fig. 1). One condition with high
relevance to oncology is infection, given the relationship be-
tween postoperative infection and poor outcomes (Scaife et al.,
2013). Surgical stress, itself even in the absence of infection, is
sufficient to trigger NETosis in liver ischemia-reperfusion
models, leading to accelerated metastatic progression (Tohme
et al., 2016). In a mouse model of intra-abdominal sepsis by
cecal ligation and puncture, it has been shown that neutrophils
exhibit enhanced NETosis, which facilitates trapping of tumor
cells in blood and aids in the establishment of hepatic metastases
(Cools-Lartigue et al., 2013). Interactions between NETs and
circulating tumor cells were achieved through the expression of
β1-integrins on tumor cells, which are upregulated in response
to infection (Najmeh et al., 2017). Infection-enhanced metastasis
can be mitigated by treatment with DNase1 in vivo, which de-
grades extracellular DNA to prevent NETs from escorting tumor
cells into the metastatic niche (Najmeh et al., 2017). Additional
studies have shown that inflammation following treatment with
bacterial LPS promotes neutrophil-mediated pulmonary metas-
tasis (Albrengues et al., 2018; El Rayes et al., 2015). This occurs in
part by triggering NETosis, which enables dormant metastatic
cells to re-engage their proliferative capacity (Albrengues et al.,
2018) or by enhanced degranulation, resulting in secretion of
proteases, such as elastase and cathepsin-G, that cleave anti-
tumorigenic thrombospondin-1 (Tsp-1; El Rayes et al., 2015).
Given the diversity of neutrophil states, an open question is
whether neutrophils uniformly respond to infection. Single-cell
RNA-seq has shown that although bacterial infection primes
neutrophils for activation at the transcriptional level, it does not
affect core gene signatures that distinguish subpopulation
identities (Xie et al., 2020). However, it is unclear which sub-
population of neutrophils is primarily responsible for cancer-
associated NETosis and how this may change during infection.
Outside the context of cancer, it is established that bacterial in-
fection and sepsis promote NETosis (Barnes et al., 2020;
Brinkmann et al., 2004; Fuchs et al., 2007; Ode et al., 2018;
Pilsczek et al., 2010; Qiang et al., 2013; Yipp et al., 2012); for ex-
ample, in mouse models of hemorrhagic and septic shock, extra-
cellular cold-inducible RNA-binding protein, an endogenous
damage-associated molecular pattern, stimulates a unique subset
of ICAM1+ neutrophils to exhibit enhanced NETosis and reverse-
transmigration (Chen et al., 2021; de Oliveira et al., 2016; Jin et al.,
2019; Murao et al., 2020; Takizawa et al., 2021). Whether ICAM1+
neutrophils play a specialized role during cancer metastasis by
virtue of their inflammatory properties remains unknown.
Cigarette smoke is another external stimulus that has sys-
temic effects on host immune responses and is the leading
preventable risk factor for cancer mortality, accounting for
∼30% of all cancer deaths. In addition to direct genotoxic effects
of cigarettes on the lung epithelium, there are dramatic effects
on the lung immune landscape. Nicotine promotes the recruit-
ment of N2-like neutrophils to the pre-metastatic lung, where
they support mesenchymal-to-epithelial transition of incoming
tumor cells, thereby facilitating colonization (Tyagi et al., 2021).
Exposing mice to nicotine or tobacco also causes neutrophils to
undergo NETosis (Albrengues et al., 2018; Hosseinzadeh et al.,
2016). Proteases within NETs, including neutrophil elastase and
MMP9, subsequently cleave laminin within the extracellular
matrix to facilitate integrin signaling and proliferation of dor-
mant cancer cells within the lung (Albrengues et al., 2018).
Genotoxic properties of additional components of cigarette
smoke, such as urethane, may also be amplified by neutrophils.
Urethane directly induces neutrophil ROS, which exacerbates
DNA damage and proliferation of the lung epithelium (Wculek
et al., 2020). As a consequence, urethane-induced lung tumor-
igenesis is blunted in neutropenic Gcsf−/− mice, and remarkably,
when neutrophils are transiently replenished with recombinant
G-CSF treatment during urethane exposure (∼1 wk), this is
sufficient to rescue lung tumorigenesis up to 4 mo later (Wculek
et al., 2020). These findings implicate neutrophils in tumor in-
itiation in smokers’ lungs and corroborate previous work
showing a role for neutrophils during neoplastic transformation
in other tissues (Antonio et al., 2015; Katoh et al., 2013).
Finally, obesity is another major contender for the top
modifiable risk factor for cancer incidence and mortality, esti-
mated to be responsible for up to ∼20% of all cancer deaths
(Calle et al., 2003; Lauby-Secretan et al., 2016; Petrelli et al.,
2021). The adipose tissue microenvironment undergoes wide-
spread immunological remodeling during weight gain, which
regulates systemic inflammatory changes that contribute to
metabolic syndrome (Brestoff and Artis, 2015; Hildreth et al.,
2021; Jaitin et al., 2019; Vijay et al., 2020). In the non-tumor
bearing setting, obesity stimulates myelopoiesis to yield ele-
vated neutrophils and Gr1+ cells in multiple organs (Nagareddy
et al., 2014; Xia et al., 2011). Lung neutrophils from obese and
lean mice have a highly divergent transcriptome, with a sig-
nificant enrichment in pathways related to oxidative stress in
obese hosts coinciding with enhanced NETosis (McDowell et al.,
2021). In cancer, both genetic- and diet-induced obesity models
have elevated peripheral and pulmonary neutrophils that
promote breast cancer metastasis to the lung in a GM-
CSF–dependent manner (McDowell et al., 2021; Quail et al.,
2017). Similar findings have been reported in murine models
of high fat diet–induced hypercholesterolemia, where the cho-
lesterol metabolite 27-hydroxycholesterol supports neutrophil
recruitment to distal sites to promote metastasis (Baek et al.,
2021; Baek et al., 2017; Ma et al., 2020). Consistently, it has
been shown that a high-fat diet promotes the accumulation of
Gr1+ myeloid cells within multiple tissues concomitant with
suppressed CD8+ T cells and enhanced cancer progression
(Clements et al., 2018; Ringel et al., 2020; Xia et al., 2011). In a
liver cancer model driven by non-alcoholic fatty liver disease/
non-alcoholic steatohepatitis, live imaging studies have shown
that a high-fat diet promotes neutrophil infiltration into the
liver, and that treatment with the anti-diabetic drug metformin
is sufficient to reverse this effect and reduce early cancer pro-
gression (de Oliveira et al., 2019). Human studies have similarly
found that obesity is associated with peripheral neutrophilia
(Herishanu et al., 2006) concomitant with elevated markers of
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neutrophil activation such as myeloperoxidase and neutrophil
elastase (Ali et al., 2018; Xu et al., 2015). Importantly, obesity
interventions, such as bariatric surgery (Adams et al., 2007;
Sjostrom et al., 2007), exercise (Moore et al., 2016), or diet
(Toledo et al., 2015), have been linked to reduced cancer inci-
dence and/or mortality in association with decreased circulating
inflammatory markers.
Taken together, many host conditions influence neutrophil
heterogeneity and function—this includes infection, smoking,
and obesity as discussed, but also extends to other chronic in-
flammatory conditions (Mistry et al., 2019; Wang et al., 2020b),
seasonal viral infections (Jenne and Kubes, 2015; Tate et al.,
2009; Toussaint et al., 2017), the gut microbiome (Zhang and
Frenette, 2019), severe COVID-19 (Barnes et al., 2020; Wilk
et al., 2020; Zuo et al., 2020a), and stress (Ince et al., 2018),
among other factors. The combination of pathogens and in-
flammatory stimuli we are exposed to throughout life is unique
between individuals and contributes to trained immunity.
Moreover, the effects of cancer genotypes compounded with
diverse host conditions and environmental exposures underlie
highly complex neutrophil heterogeneity, as has been observed
by many groups. The role that each of these different factors
plays in tumor progression is a growing area of investigation.
Neutrophils with an anti-tumorigenic phenotype: An emerging
paradox
It has been paradoxically observed that tumor-associated neu-
trophils can be protective against cancer. In some cases, tumor
cells succumb to neutrophil cytotoxicity and are thus effectively
cleared. Neutrophil tumoricidal functions can be blunted by
catalase (Granot et al., 2011), suggesting a role for H2O2. Con-
sistently, elevated expression of the H2O2-dependent calcium
channel, transient receptor potential cation channel-M2, sensi-
tizes metastatic tumor cells to neutrophil cytotoxicity, while
sparing cells at the primary tumor site (Gershkovitz et al.,
2018a). The discrepancy in susceptibility to neutrophil cyto-
toxicity in primary versus secondary tumors can be explained in
part by cellular functions required for dissemination; metastatic
tumor cells become susceptible to neutrophil cytotoxicity follow-
ing epithelial-to-mesenchymal transition (Gershkovitz et al.,
2018b), a process regulated by TGF-β signaling, echoing earlier
studies implicating this pathway in neutrophil functional diversity
(Fridlender et al., 2009; Sagiv et al., 2015). Beyond oxidative stress,
neutrophils utilize additional ammunition to kill tumor cells, in-
cluding granule enzymes such as elastase (Cui et al., 2021) or
cathepsin-G (Sionov et al., 2019). In addition, neutrophils can kill
antibody-opsonized tumor cells via trogocytosis (Bouti et al., 2021;
Martinez Sanz et al., 2021; Mart´ınez-Sanz et al., 2021; Matlung
et al., 2018), which could translate to tumor-targeting antibody
therapeutics. These studies suggest that harnessing neutrophil
tumoricidal functions, including innate immune checkpoints
(Matlung et al., 2017), may help combat cancer. However, they
also exemplify that some neutrophil-derived mediators, such as
elastase or ROS, can elicit both pro- and anti-tumoral effects
depending on context—a concept that is still a puzzle in the field.
Complementing cytotoxicity, neutrophils can conspire with
the adaptive immune system to facilitate tumor cell recognition
and clearance. Co-culture experiments using cells from early-
stage human lung cancer have shown that tumor-associated
neutrophils enhance T cell activation compared to their blood-
borne counterparts (Eruslanov et al., 2014). In turn, activated
T cells prolong the lifespan of neutrophils in vitro and upregu-
late co-stimulatory molecules on the neutrophil plasma mem-
brane, leading to a positive-feedback loop that perpetuates T cell
stimulation (Eruslanov et al., 2014). In subsequent work, a
specialized subset of tumor-associated HLA-DR+ neutrophils
was identified in early-stage tumors, which is capable of cross-
presenting exogenous tumor antigens to CD8+ T cells to stimu-
late tumor-specific effector T cell responses (Singhal et al.,
2016). Others have similarly reported that FcɣR engagement
converts neutrophils into antigen presenting cells that cross-
present to CD8+ T cells to induce anti-tumor immunity in mel-
anoma models (Mysore et al., 2021). However, over time, the
ability of tumor-associated neutrophils to engage adaptive im-
mune pathways declines as tumors progress (Singhal et al.,
2016). These data support a model where neutrophils undergo
an immunogenic “switch” from anti-tumorigenic to pro-
tumorigenic as cancer advances; however, this temporal re-
sponse may be context specific. For example, in mouse models of
melanoma, neutrophils maintain some anti-tumorigenic prop-
erties in the advanced disease under specific therapeutic set-
tings. Combining a triple therapy of chemotherapy, infusion of
CD4+ T cells specific to the melanoma antigen Trp1, and co-
stimulation or immune checkpoint blockade is sufficient to
eliminate tumors, due to a significant infiltration of neutrophils
that exhibit anti-tumor behavior (Hirschhorn-Cymerman et al.,
2012; Hirschhorn-Cymerman et al., 2020). The increase in these
anti-tumorigenic neutrophils was associated with an increase in
cutaneous immune adverse events. In human melanoma sam-
ples, treatment with immune checkpoint inhibitors is associated
with enhanced NETosis, which has been proposed as a potential
mechanism to eradicate tumor antigen escape variants that arise
in response to treatment selection pressure (often in concordance
with immune-related adverse events; Hirschhorn-Cymerman
et al., 2020). Although many studies have characterized the role
of neutrophils in cancer progression, how neutrophils are altered
in response to specific therapies at different stages of disease re-
mains unanswered and needs further exploration.
Many anti-tumorigenic neutrophil functions have been de-
scribed in humans, raising questions about species-specific roles
in cancer (Eruslanov et al., 2017). Single-cell RNA-seq of human
and mouse neutrophils from lung tumors showed considerable,
but not complete, overlap between species (Zilionis et al., 2019).
At the functional level, several differences have been reported.
First, the NETosis potential of circulating neutrophils frommice
versus patients with cancer is distinct, including their ability to
release NETs in response to G-CSF (Arpinati et al., 2020). Sec-
ond, the tumoricidal functions of neutrophils may be species
specific, based on differences in their granule/secretory profile
(Cui et al., 2021; Rausch and Moore, 1975) or utilization of dis-
tinct ROS pathways (Bagaitkar et al., 2012). Third, mouse and
human neutrophils differ in their expression of Arg-1 and ability
to metabolize arginine (Jacobsen et al., 2007; Munder et al.,
2005; Rodriguez et al., 2007). This could affect T cell
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responses, as decreased arginine availability in the tumor mi-
croenvironment is associated with T cell immunosuppression.
Another explanation for the protective role of neutrophils in
cancer is the possibility of stage-dependent enrichment for
specific neutrophil states. For example, when comparing the
immune infiltrate of highly and poorly metastatic murine tu-
mors, both increase myeloid infiltration in the pre-metastatic
lung; however, poorly metastatic tumors also secrete prosapo-
sin, which induces Tsp-1 expression in lung-infiltrating Gr1+ cells
to impair metastasis (Catena et al., 2013; Wang et al., 2016).
Similar mechanisms between early and advanced tumors in
patients have yet to be compared.
Neutrophil heterogeneity is observed throughout granulopoiesis
A major source of neutrophil heterogeneity comes from the
dynamics of their maturation and release from BM. Neutrophils
arise from HSCs in BM, which give rise to multipotent progen-
itors, then commonmyeloid progenitors, granulocyte–monocyte
progenitors (GMPs), and neutrophil-committed precursors
(Table 1). This linear model may in part underlie our confounded
understanding of neutrophil heterogeneity, as neutrophil on-
togeny and phenotypic plasticity are likely to be more complex.
Learning from other myeloid lineages, monocyte heterogeneity
and functionality reflect both ontogeny and response to micro-
environmental stimuli. Inflammatory monocytes can arise in-
dependently from both GMPs and monocyte–dendritic cell
progenitors (MDPs), where GMPs give rise to neutrophil-like
monocytes, while MDPs give rise to monocytes that can fur-
ther differentiate into dendritic cells (Yanez et al., 2017). More-
over, factors within the microenvironment confer a preference
for monocyte maturation along one of these developmental tra-
jectories; LPS favors neutrophil-like monocyte maturation from
GMPs, while exposure to CpG favors the MDP lineage (Yanez
et al., 2017). These developmental mechanisms may in part ex-
plain the functional breadth of monocyte and macrophage
identities. Indeed, the lessons that we have learned from
monocytes may be relevant to a modified understanding of
granulopoiesis and neutrophil plasticity.
In recent years, single-cell technologies have made substan-
tial advancements toward defining neutrophil maturation from
GMPs (Dinh et al., 2020; Drissen et al., 2016; Evrard et al., 2018;
Kwok et al., 2020; Olsson et al., 2016; Velten et al., 2017; Xie
et al., 2020; Zhu et al., 2018). Across studies, several new
terms have been coined for overlapping neutrophil develop-
mental states, which are in need of consolidation (Table 1 and
Fig. 2 A). In mouse BM, GMPs mature into pro-neutrophils
(proNeu [Dinh et al., 2020; Evrard et al., 2018; Kwok et al.,
2020; Muench et al., 2020], corresponding to clusters G0/G1
in similar work [Xie et al., 2020]) and then into highly prolif-
erative, poorly motile precursors (preNeu) that drive expansion
within spleen and BM (Evrard et al., 2018). Cells defined as
preNeu (Evrard et al., 2018) are transcriptionally similar to
unipotent neutrophil progenitors (NeP; Zhu et al., 2018), neu-
trophil precursors (NeuP; Kim et al., 2017), and to a G2 cluster
that resembles myelocytes/metamyelocytes (Xie et al., 2020;
also see Ng et al., 2019). Subsequently, preNeu differentiate into
immature (Ly6GintCXCR2−; immNeu) ormature (Ly6GhiCXCR2+;
mNeu) neutrophils that are non-proliferative and mediate
trafficking and effector functions (Evrard et al., 2018). ImmNeu
overlaps transcriptionally with a band cell-like G3 cluster that
expresses low Cxcr2 and high secondary granule genes (Xie et al.,
2020), and with late-stage progenitors (cluster C2; high Ly6G
expression), as confirmed by adoptive transfer experiments
with NeP (Zhu et al., 2018). Mature neutrophils correspond to
cluster G4 from Xie et al. (2020), representing the most mature
state in BM with high expression of Mmp8 and Cxcl2, while the
G5 cluster was the most mature overall and predominant in
blood (Xie et al., 2020). A summary of overlapping states can be
found in Table 1.
Neutrophil development coincides with shifts in chromatin
accessibility and transcription factor activity (Ai and Udalova,
2020; Ballesteros et al., 2020). Developmental trajectory analysis
of single-cell RNA-seq data unveiled a developmental continuum
known as “neutrotime,” which spans the maturation spectrum
from neutrophil precursors in BM to mature neutrophils in
blood and spleen (Grieshaber-Bouyer et al., 2021). The sharpest
changes in neutrotime occur during granulopoiesis (transition
from immature to mature) and mobilization (transition from
BM to blood; Grieshaber-Bouyer et al., 2021). Consistently, in
steady-state and inflammation, neutrophil chromatin land-
scapes and transcription factor networks shift in waves. In
steady-state, the initiation of granulopoiesis in BM involves
RUNX1 and C/EBPα transcription factors within GMPs, followed
by a shift to GFI1 and C/EBPε in preNeu during early neutrophil
differentiation, and then C/EBPδ and PU.1 as mNeu enter the
circulation (Evrard et al., 2018). The temporal expression of
C/EBP-family members mirrors the pattern of granule enzyme
expression; primary granule enzymes (e.g., Mpo) are expressed
at the GMP stage, secondary granules (e.g., Ltf) at the preNeu/
immNeu stage, and tertiary granules (e.g., Mmp8) at the mNeu
stage, corresponding to Cebpa, Cebpe, and Cebpd, respectively
(Evrard et al., 2018). In comparison, chromatin profiling of
neutrophils combined with genetic validation approaches has
identified transcription factors involved in neutrophil matura-
tion during acute inflammation. For example, RUNX1 and KLF6
drive neutrophil maturation in BM, and after cells are mobilized,
chromatin is remodeled to enable access by RFX2 and RELB to
promote survival (Khoyratty et al., 2021).Within tissues, another
chromatin remodeling event enables the transcriptional activity
of RELB, IRF5, and JUNB, which license innate effector functions
that are pre-programmed in early developmental stages (Khoyratty
et al., 2021). These findings echo those from earlier work describing
two major waves of chromatin remodeling between developmental
transitions from (pro)myelocyte to metamyelocytes and from seg-
mented neutrophils to polymorphonuclear neutrophils (Grassi
et al., 2018), and extend them by charting a transcriptional blue-
print for each transition. The remaining knowledge gaps include
understanding how environmental signals integrate with tran-
scription factor landscapes to yield functional outputs, and how the
release of neutrophils from BM at different maturation states is
regulated.
Functionally, there are still many unknowns surrounding
the kinetics of neutrophil maturation, trafficking, and ef-
fector function (Barros-Becker et al., 2020; Hind et al., 2021;
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Houseright et al., 2021; Klemm et al., 2021). For example, some
neutrophils are capable of reverse transmigration from inflamed
tissues back into the circulation (de Oliveira et al., 2016; Wang
et al., 2017). Moreover, in cancer, multiple neutrophil develop-
mental states co-exist: in orthotopic mouse models of pancreatic
cancer, CD101− immNeu accumulate intratumorally in associa-
tion with disease progression (Evrard et al., 2018), corroborating
studies that have reported a pro-tumorigenic role for neutrophils
with a banded (immature) nuclear morphology (Coffelt et al.,
2015; Hsu et al., 2019; Sagiv et al., 2015). Consistently, in or-
thotopic melanoma models, NeP are elevated in BM, blood, and
tumor, and they promote tumor growth in association with el-
evated expression of PD-L1 (Zhu et al., 2018). In melanoma pa-
tients, human NeP are found at higher frequencies in blood
compared to healthy donors, where they are extremely rare
(Zhu et al., 2018). Even earlier developmental stages can be
detected in blood and tumors of lung cancer patients, including
precursors to NeP/preNeu states (Dinh et al., 2020). Moreover,
extramedullary granulopoiesis has been described in the context
of cancer where neutrophil maturation in spleen yields an im-
munosuppressive phenotype (Alshetaiwi et al., 2020; Cortez-
Retamozo et al., 2012; Mastio et al., 2019). Therefore, shifts in
the developmental states of granulocytes, their premature
egress from BM at different stages (which may influence granule
cargo), and their distinct functional contributions to tumor
growth shed light on the high degree of neutrophil heteroge-
neity observed in cancer. This echoes findings in other inflam-
matory conditions, like systemic lupus erythematosus, where
Table 1. Cell surface markers defining neutrophil developmental states
Acronym Full name Function Surface markers
(mouse)
Surface markers
(human)
Overlapping states References
CMP Common myeloid
progenitors
High proliferation, low
self-renewal, multipotent
LKS− CD34int CD16/
32int Flt3+ CD115lo
Antibody combination
excludes monocyte-DC
progenitors, known as
“MDP”
Lin− CD34+ CD38+
CD45RA−
Kwok et al.,
2020; Yanez
et al., 2017
GMP Granulocyte–monocyte
progenitors
High proliferation, low
self-renewal, oligopotent
LKS− CD34+ CD16/32hi
Ly6C−
Antibody combination
excludes committed
granulocyte progenitors
and monocyte
progenitors
Lin− CD34+ CD38+
CD45RA+
Yanez et al.,
2017; Kwok
et al., 2020
proNeu1 Pro-neutrophils (stage 1) Committed progenitors;
expand in BM during
emergency
granulopoiesis at the
expense of monocytes
LKS− CD34+ CD16/32hi
Ly6C+ CD115lo CD81+
CD11b− CD106−
CD15+ CD66b+
CD11b+ CD49dhi
SSClo (also CD34lo
CD38lo)
Mouse: G0 (Xie et al.,
2020);
Human: eNeP/N1 (Dinh
et al., 2020)
Kwok et al.,
2020; Evrard
et al., 2018
proNeu2 Pro-neutrophils (stage 2) Intermediate progeny; do
not expand during
emergency
granulopoiesis
LKS− CD34+ CD16/32hi
Ly6C+ CD115lo CD81+
CD11b+ CD106+
CD15+ CD66b+
CD11b+ CD49dint
SSChi (also CD34−
CD38−)
Mouse: G1 (Xie et al.,
2020);
Human: N1 (Dinh et al.,
2020)
Kwok et al.,
2020; Evrard
et al., 2018
preNeu Neutrophil precursors High proliferation, low
motility, low effector
functions; expand in BM
and spleen during
emergency
granulopoiesis
LCS− cKitint Ly6C+
CD11b+ Ly6Glo CXCR2−
CXCR4hi
CD15+ CD66b+
CD11b+ CD49dint
CD101−
Mouse: G2 (Xie et al.,
2020), NeuP (Kim et al.,
2017), C1/NeP (Zhu et al.,
2018);
Human: N2 (Dinh et al.,
2020)
Kwok et al.,
2020; Evrard
et al., 2018
immNeua Immature neutrophils Intermediate
proliferation, motility and
effector functions
LCS− cKitlo Ly6Clo
CD11b+ Ly6Gint CXCR2−
CXCR4lo
CD15+ CD66b+
CD11b+ CD49d−
CD101+ CD16int
CD10−
Mouse: G3 (Xie et al.,
2020), C2 (Zhu et al.,
2018);
Human: N3 (Dinh et al.,
2020)
Kwok et al.,
2020; Evrard
et al., 2018
mNeua Mature neutrophils Low proliferation, high
motility, high effector
functions
LCS− cKit− Ly6Clo
CD11b+ Ly6Ghi CXCR2+
CXCR4−
CD15+ CD66b+
CD11b+ CD49d−
CD101+ CD16hi
CD10+
Mouse: G4 (BM) and G5
(blood; Xie et al., 2020);
Human: N4 and 5 (Dinh
et al., 2020)
Kwok et al.,
2020; Evrard
et al., 2018
LKS+, Lin− cKit+ Sca1+; LKS−, Lin− cKit+ Sca1−; LCS−, Lin− CD115− SiglecF−; Lin, cocktail of lineage marker antibodies, which should include anti-CD11b up to the
GMP stage, but exclude it for analysis of proNeu-mNeu.
aCXCR2 can be downregulated within tumors; to define mouse immNeu and mNeu in this context, CD101 can be used (CD101− immNeu and CD101+ mNeu;
Evrard et al., 2018).
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distinct neutrophil states identified through single-cell RNA-seq
uniquely regulate disease pathogenesis (Mistry et al., 2019).
Finally, it remains unknown how trained immunity at the
individual (host) level may influence this complex system.
Studies in animal and plant models that lack adaptive immunity
have shown that innate immune cells or their developmental
precursors can become “trained” following exposure to an in-
flammatory stimulus, resulting in an altered response to sec-
ondary challenges even after cells have returned to a resting
state (Chavakis et al., 2019; Netea et al., 2020). Trained
Figure 2. Neutrophil maturation and activation. (A) Comparison of neutrophil states described in landmark studies using single-cell analyses. Overlaid are
transcriptional states in normal development and cancer, cell morphology (morph), transcription factor (TF) activity in steady-state (SS) and acute inflam-
mation (AI), neutrotime developmental transition waves, and anatomical location. MB/PM, myeloblasts and promyelocytes; MC, myelocytes; MM, meta-
myelocytes; BC/SC, band cells and segmented neutrophils. (B) Projection of MDSC single-cell RNA-seq data from Veglia et al. (2021a) onto established
neutrophil states (comparative datasets obtained from Xie et al. [2020], Immgen [Aran et al., 2019], and Ballesteros et al. [2020]). All intratumoral poly-
morphonuclear populations referred to as MDSC express canonical signatures of neutrophil maturation and identity states. Created with BioRender.com.
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immunity is thus different between individuals, depending on
history of pathogen exposures, vaccination, cancer, or other
inflammatory stimuli. Indeed, studies have identified β-glucan,
Bacillus Calmette-Gue´rin, and other vaccines as prototypical
agonists of trained immunity, mediated by education of myeloid
cells within the BM and myeloid-bias progenitor expansion
(Kaufmann et al., 2018; Mitroulis et al., 2018); however, trained
immunity can also be achieved through sterile triggers, such as
diet-induced changes to myeloid progenitor reprogramming
(Christ et al., 2018). Recent studies have explored the role of
trained immunity in cancer in the context of granulopoiesis.
β-glucan induces myeloid expansion concomitant with elevated
innate immune signaling mediators, such as IL-1β and GM-CSF
(Mitroulis et al., 2018), which mediate neutrophil expansion in
tumors. Treatment of mice with β-glucan 1 wk prior to subcuta-
neous inoculation of B16F10 melanoma or Lewis lung carcinoma
lung cancer cells into syngeneic hosts blunts tumor growth, even in
Rag1−/− mice that lack T and B cells (Kalafati et al., 2020). Mecha-
nistically, β-glucan causes epigenetic and transcriptomic re-
programming of granulopoiesis, yielding progenitor cells with
enhanced IFN signaling and tumoricidal mature neutrophils with
elevated ROS (Kalafati et al., 2020).Moreover, the anti-tumor effect
of β-glucan is maintained and transferrable following BM trans-
plantation or neutrophil adoptive transfer from β-glucan–treated
donor mice into naive recipients (Kalafati et al., 2020). Outside the
context of cancer, activated neutrophils can prime macrophages to
exhibit long-term responses against parasitic infection (Chen et al.,
2014), raising the possibility that neutrophils may participate in
training of other myeloid cells in tumors. These findings support
the notion that myeloid-targeted immunotherapies that aim to re-
program, rather than deplete, target cells are an attractive thera-
peutic approach to harnessing anti-tumor immunity.
Discrepancies in neutrophil research and proposed solutions
Owing to the complexity of neutrophil diversity, it is not sur-
prising that we have encountered several experimental dis-
crepancies as a field. First, amongst many possible functional
states, neutrophils can be immunosuppressive, thus challenging
the designation of granulocytic myeloid-derived suppressor cells
(G-MDSCs; also known as PMN-MDSC) as a distinct population.
G-MDSC and neutrophils are indistinguishable by archetypal
cell surface markers and have identical granular and nuclear
morphologies. Moreover, there are no genetic models to trace or
target G-MDSCs due to lack of genetic differences from neu-
trophils. Instead, antibody depletion via anti-Gr1 or anti-Ly6G is
often used to test their functional role in disease; however, these
antibodies also deplete neutrophils, making causative functional
assessment of MDSCs uninterpretable. For associative func-
tional studies, it has been suggested that identification of MDSCs
requires confirmation of immunosuppression ex vivo (Bronte
et al., 2016; Veglia et al., 2021b), but often cell surface markers
are used alone. Single-cell RNA-seq studies have attempted to
identify MDSC in tumors (Veglia et al., 2021a); however, puta-
tive G-MDSCs share transcriptional similarities with canonical
neutrophils as defined by Immgen (Heng et al., 2008), as well as
signatures of mature neutrophils (Evrard et al., 2018; Xie et al.,
2020) across multiple tissues (Ballesteros et al., 2020; Fig. 2 B).
Given the diversity of neutrophil identities, which can include
immunoregulatory functions, it remains controversial whether
G-MDSCs should simply be called “immunosuppressive neu-
trophils” and thus terminology is used inconsistently between
groups. Although putative surface markers have been identified
to distinguish G-MDSC and neutrophils such as CD84, CD14,
FATP2, or LOX-1 (Alshetaiwi et al., 2020; Condamine et al., 2016;
Veglia et al., 2021a; Veglia et al., 2019), these have not been used
by the broader research community and they may be expressed
by bona fide neutrophils under certain conditions. Given the
lack of existing genetic and phenotypic markers to distinguish
bona fide neutrophils from putative G-MDSC, it has been sug-
gested that the monolithic MDSC terminology be dropped in
favor of a more colorful view of myeloid biology that embraces
the high degree of cellular and functional heterogeneity (Hegde
et al., 2021). We support this view and urge scientists to consider
the literature on both neutrophils and G-MDSCs to inform on-
going research within these evolving fields.
Second, antibody-mediated neutrophil depletion has context-
dependent efficacy. The most common antibodies used are anti-
Ly6G (clone 1A8, rat IgG2a) and anti-Gr1 (clone RB6-8C5, rat
IgG2b); anti-Ly6G is often preferred since mature neutrophils
are Ly6G+/hi, while Gr1 also targets monocytes, some immature
myeloid cells, and even a subset of CD8+ memory T cells by
virtue of Ly6C expression. However, in C57BL/6 mice, anti-Gr1
effectively ablates neutrophils, whereas anti-Ly6G is less effec-
tive because depletion is slower than neutrophil repopulation
from BM (Boivin et al., 2020; Faget et al., 2018 Preprint). Despite
this, numerous studies have used anti-Ly6G to deplete neu-
trophils successfully, suggesting that experimental design is key:
first, dose and duration are variables that affect any mAb-based
depletion approach. Short-term experiments (1–2 d) with anti-
Ly6G result in highly effective neutrophil depletion (Deniset
et al., 2017; Lee et al., 2018; Siwicki et al., 2021); however, in
longer trials (>3–7 d), neutrophil numbers may begin to rebound
(Deniset et al., 2017; Moses et al., 2016). Second, there are dif-
ferences in neutrophil depletion efficacy depending on experi-
mental context. Comparative analyses with anti-Gr1 and anti-Ly6G
mAbs showed enhanced depletion in Balb/c and FVB/n back-
grounds compared to C57BL/6, especially when C57BL/6micewere
aged (Boivin et al., 2020; Faget et al., 2018 Preprint). Moreover,
neutrophils are more difficult to eliminate in certain tissues, such
as BM (Pollenus et al., 2019). Third, for experimental contexts in
which anti-Ly6G is ineffective, a more durable protocol has been
developed via co-administration of rat anti-mouse Ly6G and anti-
rat mAbs, which enhance the killing efficacy of anti-Ly6G to de-
plete neutrophils for at least 18 d in C57BL/6 models (Boivin et al.,
2020; Faget et al., 2018 Preprint). Finally, neutrophil depletion ef-
ficacy cannot be validated using anti-Ly6G (1A8), as antigen
masking produces false-negative staining (Boivin et al., 2020).
Alternative strategies include intracellular Ly6G staining, histology
for myeloperoxidase (MPO) or neutrophil elastase (NE), or re-
portermice, such as LysM-cre or Ly6G-cre, combinedwith Ly6Clo/int,
and side scatter assessment (Boivin et al., 2020; Deniset et al., 2017;
Hasenberg et al., 2015). Genetic neutrophil depletion approaches,
as discussed below, may also provide functional confirmation of
antibody effects (Ballesteros et al., 2020).
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Common genetic approaches to target or deplete neutrophils
in vivo include theMrp8-cremodel (Passegue et al., 2004), either
combined with a specific floxed allele or ROSA-DTA mice (cre-
dependent expression of diphtheria toxin), respectively. The
Mrp8-cre model targets ∼80% of mature neutrophils in vivo;
however, Mrp8 is also expressed in 10–20% of GMPs (Passegue
et al., 2004). Alternatively, the Ela2-cre model targets mature
neutrophils expressing elastase, a serine protease within neu-
trophil primary granules (Tkalcevic et al., 2000; Wculek and
Malanchi, 2015). Newer models, such as the Ly6G-cre mouse
(Hasenberg et al., 2015), offer a more specific alternative;
however, the efficacy of recombination is purportedly allele-
specific depending on the particular floxed strain being used.
Further, activation of recombinase under control of this gene
occurs late in neutrophil development, such that proteins al-
ready produced may persist for the short lifetime of the cell. For
combinations with fluorescent reporter strains for intravital
microscopy or other imaging modalities (such as the Ai9 cre
reporter mouse), the Ly6G-cre mouse is an excellent option for
neutrophil-specific tracing (Hasenberg et al., 2015). However,
for gene deletion studies, this model should be used in parallel
withMrp8-cre or Ela2-cre, and recombination should be carefully
validated.
Third, methods to target NETosis have raised debate within
the field. Genetic knockout studies have shown that protein
arginine deiminase 4 (PAD4) is required for nuclear deconden-
sation and nuclear rupture preceding NETosis (Li et al., 2010).
Yet, some studies have found that targeting PAD4 is effective
against NETosis (Hemmers et al., 2011; Li et al., 2010; Martinod
et al., 2013; Munzer et al., 2021; Thiam et al., 2020), while others
have not (Claushuis et al., 2018; Guiducci et al., 2018; Kenny
et al., 2017; Tsourouktsoglou et al., 2020). There are several
plausible explanations for this discrepancy: First, some defining
features of NETosis can be mimicked in other contexts. Exam-
ples include leukotoxic hypercitrullination (involving non-
bactericidal hyperactivation of PAD leading to DNA extrusion),
constitutively defective mitophagy (resulting in mitochondrial
DNA expulsion; Caielli et al., 2016; Lood et al., 2016; Yousefi
et al., 2009), or epigenetic regulation of pluripotency
(whereby PAD4-mediated citrullination promotes an open
chromatin structure; Christophorou et al., 2014). Thus, a stan-
dardized readout for NETosis is needed. Although citrullinated
histone H3 (H3cit) is a reasonably specific marker for NETs in
disease models since PAD4 deficiency/inhibition prevents cit-
rullination of histones, histological assessment of NE or MPO
associated with extracellular DNA is required to measure NETs
in the context of PAD4 blockade. Second, NETosis may not al-
ways rely on PAD4, as observed in models of pneumosepsis
(Claushuis et al., 2018). NETosis can be NOX2 dependent (in-
duced by phorbol esters, LPS, etc.) or NOX2 independent (in-
duced by calcium ionophores, UV light, etc.; Douda et al., 2015;
Fuchs et al., 2007; Lood et al., 2016; Parker et al., 2012; Pilsczek
et al., 2010). Hypercitrullination of histones only occurs during
calcium ionophore-activated NETosis, suggesting PAD4 may
contribute specifically to NOX2-independent NETosis (Douda
et al., 2015; Khan and Palaniyar, 2017). Third, mouse back-
ground strain may influence PAD4 dependency. C57BL/6 mice
have a Th1-type bias, whereas other strains tend to favor Th2
responses, therefore, we recommend that background strains be
reported in publications. Finally, PAD4 reliance may be context
dependent. For example, “aged” neutrophils exhibit lower
NETosis than “fresh”neutrophils newly released fromBM (Adrover
et al., 2019); neutrophils responding to bacterial infection ex-
hibit pronounced NETosis compared with those responding to
sterile injury (Yipp et al., 2012); and PAD4 inhibitor efficacy may
have species-specific variation (Arpinati et al., 2020; Lewis et al.,
2015). Of note, it is uncertain how targeting NETs might impact
innate immune responses in humans, given their role in auto-
immunity (Khandpur et al., 2013; Li et al., 2020), aging
(Martinod et al., 2017), emergency granulopoiesis, vascular in-
flammation (Knackstedt et al., 2019), and other inflammatory
conditions (Jorch and Kubes, 2017; Papayannopoulos, 2018;
Phillipson and Kubes, 2011). This question is being addressed for
the first time in patients with severe COVID-19 who exhibit el-
evated NETosis (Ackermann et al., 2021; Barnes et al., 2020;
Middleton et al., 2020; Zuo et al., 2020b Preprint), which will
provide insight for cancer patients.
Concluding remarks: Open questions in neutrophil biology
and cancer
Going forward, it will be critical to reconsider how neutrophils
are classified and studied in the laboratory setting. First, there is
a knowledge gap in reconciling the root cause of neutrophil
heterogeneity. Adopting principles from the mononuclear
phagocyte system, in which cells are classified developmentally
and phenotypically (Guilliams et al., 2014), may help clarify
tissue-specific neutrophil biology in steady-state and inflamma-
tion. Although neutrophils originate from definitive hematopoie-
sis, efforts in this direction are now emerging (Evrard et al., 2018;
Kim et al., 2017; Muench et al., 2020; Zhu et al., 2018), and there is
a growing appreciation that functionally distinct developmental
identities can co-exist in cancer. We propose to use the terms
“states” to refer to phenotypically distinct neutrophil populations,
including those that are immunosuppressive since it is the envi-
ronment that appears to drive neutrophil heterogeneity via shifts
in maturation and/or activation.
Second, there is a need to standardize techniques. This in-
cludes methods to deplete neutrophils with antibodies, dis-
criminate between neutrophil states, and validate NET targeting
approaches. Of note, currently, the preferred methods for NET
detection are immunohistochemistry (association of MPO, NE,
or Ly6G with extracellular DNA, or H3cit in the presence of
MPO/DNA complexes) or dual-target ELISA (e.g., anti-elastase
and anti-DNA-peroxidase), and new detection tools are emerg-
ing, including antibodies against histone H3 cleavage events
specific to NETs in humans (Tilley et al., 2021 Preprint). How-
ever, alternative approaches are readily used, including H3cit
ELISA/immunohistochemistry or flow cytometry for different
combinations of MPO, H3cit, and/or SYTOX viability dyes, while
these provide reasonable estimates, they are not conclusive.
Although we see value in these techniques under certain cir-
cumstances, for example, to analyze limited patient material, we
recommend that orthogonal approaches to validate findings are
employed.
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Third, most studies are focused on bulk analysis of neu-
trophils. However, single-cell technologies can resolve shifts in
the relative proportions of neutrophil states that co-exist outside
the BM. Using these datasets to map differentiation trajectories
and epigenetic regulation of neutrophil development using
single-cell assay for transposase-accessible chromatin sequenc-
ing may also reveal relationships not evident from the tran-
scriptome. These efforts will be particularly informative to
understand molecular mechanisms and transcriptional regu-
lators that govern neutrophil maturation and function (Evrard
et al., 2018; Muench et al., 2020; Weiss et al., 2015). Moreover,
they will allow us to resolve nomenclature for various neutro-
phil developmental stages (see Table 1 and Ng et al., 2019). In
addition, in vivo techniques to trace or target individual cell
subsets would be of value (Harvie and Huttenlocher, 2015). For
example, three neutrophil states are conserved within tumors in
both humans and mice (Zilionis et al., 2019). Whether these
neutrophil states are functionally plastic and/or whether they
can be individually targeted has yet to be determined.
Finally, our knowledge of neutrophils in cancer largely de-
pends on data from murine models. However, it is clear that
there are some species-specific differences in neutrophil regu-
lation of tumor biology. In human studies, most experimental ap-
proaches are limited to ex vivo analyses of blood neutrophils,
transcriptomic profiling of tumor-associated neutrophils, and basic
correlations with clinical outcomes. Although these approaches are
informative, they shed light on disease association and not causa-
tion. Therefore, a comprehensive understanding of the functional
impact of human neutrophils on cancer is lacking and needs to be
further elucidated to develop relevant therapeutic strategies.
Taken together, our fundamental understanding of neutro-
phil maturation, heterogeneity, and function in the context of
cancer has recently seen remarkable advances with emerging
fate-tracing, high-parameter, and single-cell technologies that
are now allowing us to study fundamental neutrophil biology at
unprecedented depth. The next challenge is to reconcile existing
data and unify nomenclature so that our collective discoveries
can be integrated and directly compared. Ultimately, we aim to
harness our emerging understanding of neutrophil phenotypic
heterogeneity to characterize neutrophil states at the functional
level, and effectively exploit them for therapeutic purposes.
Acknowledgments
This consensus statement is dedicated to our esteemed col-
leagues, Zena Werb and Paul S. Frenette, who attended and
participated in the Banbury Center meeting and encouraged a
collective effort by attendees to write this report. Both made
significant contributions to ideas and discussions that are
represented here.
The Banbury Center meeting was organized byM. Egeblad, P.
Kubes, K.E. de Visser, R. Leshan, and Banbury Center staff. The
meeting was supported financially by Cold Spring Harbor Lab-
oratory Northwell Health Affiliation. The funder had no in-
volvement with the writing of this consensus statement. D.F.
Quail acknowledges funding from the Canadian Institutes of
Health Research (PJT-159742, PJT-178306), Terry Fox Research
Institute, and Tier II Canada Research Chair. B. Amulic ac-
knowledges funding from the Medical Research Council (MR/
R02149x/1). M. Aziz acknowledges funding from the National
Institutes of Health (NIH; R01GM129633). B.J. Barnes acknowl-
edges funding from the NIH National Institute of Arthritis and
Musculoskeletal and Skin Diseases (AR065959-01) and Depart-
ment of Defense (CDMRP LRP W81XWH-18-1-0674). E. Erusla-
nov acknowledges funding from the NIH National Cancer
Institute (NCI; R01CA187392) and the Department of Defense
(CDMRP W81XWH-15-1-0717). Z.G. Fridlender acknowledges
funding from the the Israel Science Foundation (grant number
1708/20) and the Sasson and Luisa Naor Fund. H.S. Goodridge
acknowledges funding from the NIH National Institute of Al-
lergy and Infectious Diseases (R01AI134987). Z. Granot ac-
knowledges funding from the Israel Science Foundation Grant
405/18, the Israel Cancer Research Fund, the Deutsche For-
schungsgemeinschaft, and the Rosetrees Trust. A. Hidalgo ac-
knowledges funding from FET-OPEN (861878) from the
European Commission; the Centro Nacional de Investigaciones
Cardiovasculares (CNIC) is supported by the Ministerio de
Ciencia e Innovación and the Pro-CNIC Foundation. M.J. Kaplan
acknowledges funding from the Intramural Research Program of
the NIH, National Institute of Arthritis and Musculoskeletal and
Skin Diseases (ZIAAR041199). I. Malanchi acknowledges funding
from the European Research Council grant (ERC CoG-H2020-
725492) and from the Francis Crick Institute, which receives its
core funding from Cancer Research UK (FC001112), the UK
Medical Research Council (FC001112), and the Wellcome Trust
(FC001112). T. Merghoub acknowledges funding from the NIH/
NCI Cancer Center Support Grant (P30 CA008748/NCI R01
CA056821), Swim Across America, Ludwig Institute for Cancer
Research, Ludwig Center for Cancer Immunotherapy at Memo-
rial Sloan Kettering, Cancer Research Institute, and Parker In-
stitute for Cancer Immunotherapy. E. Meylan acknowledges
funding from the Swiss National Science Foundation
(310030_179324) and Fonds de la Recherche Scientifique (MISU
F.6003.22). M.J. Pittet acknowledges funding from the Institut
Suisse de Recherche Expe´rimentale sur le Cancer Foundation,
Ludwig Cancer Research, and the NIH (P01CA240239,
R01CA218579). I.A. Udalova acknowledges funding from the
Wellcome Trust Investigator Award (209422/Z/17/Z). T.K. van
den Berg acknowledges funding from Byondis BV, the Dutch
Ministry of Health, and the Dutch Cancer Society (10300). D.D.
Wagner acknowledges funding from the NIH National Health,
Lung and Blood Institute (R35HL135765). P. Wang acknowledges
funding from the NIH National Institute of General Medical Sci-
ences (R35GM118337). A. Zychlinsky acknowledges funding from
the Max Planck Society. K.E. de Visser acknowledges funding from
the Dutch Cancer Society (KWF10623, KWF10083, and KWF13191),
Oncode Institute, and the Netherlands Organization for Scientific
Research (NWO-VICI 91819616). M. Egeblad acknowledges funding
from the Department of Defense, Congressional Directed Medical
Research Program (W81XWH2010753). P. Kubes acknowledges
funding from the Canadian Institutes of Health Research.
Author contributions: A. Rubio-Ponce performed computa-
tional analysis included in Fig. 1 B. All other authors attended
Banbury Center meeting on Diverse Functions of Neutrophils in
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Cancer, and this manuscript reflects an updated perspective on key
areas of discussion. K.E. de Visser, M. Egeblad, and P. Kubes contrib-
uted to the conceptualization, design, and organization of the meeting.
D.F. Quail collated and summarized written and verbal meeting notes
fromattendees; all authorswhoattended themeeting contributed ideas
and assisted with writing, editing, and revising the manuscript.
Disclosures: E. Eruslanov reported a patent to the use of HLA-
DR+CD32hiCD64hi hybrid neutrophils with characteristics of
antigen-presenting cells to augment therapy for cancer or in-
fectious diseases pending. Z.G. Fridlender reported “other” from
Immunyx outside the submitted work; in addition, Z.G. Frid-
lender had a patent to ID - 6494-1 licensed "Immunyx." Z. Granot
reported personal fees from Immunyx Pharma outside the
submitted work. A. Hidalgo is a paid consultant for Flagship
Pioneering, which is not related to this work. M.J. Pittet reported
personal fees from AstraZeneca, Debiopharm, Elstar Therapeu-
tics, ImmuneOncia, KSQ Therapeutics, MaxiVax, Merck, Mo-
lecular Partners, Third Rock Ventures, and Tidal outside the
submitted work; in addition, M.J. Pittet has been a consultant for
Aileron Therapeutics, Cygnal Therapeutics, and Siamab Thera-
peutics. T.K van den Berg is an inventor on patent application
WO2009/131453 A1, owned by Sanquin Blood Supply Organi-
zation, licensed to Byondis BV, related to the targeting of CD47-
SIRPα in cancer. D.D. Wagner reported personal fees from
Takeda Pharmaceutical and “other” from Neutrolis, SAB during
the conduct of the study. K.E. de Visser reported grants from
Roche/Genentech and personal fees from Macomics outside the
submitted work. M. Egeblad is a member of the research advi-
sory board for brensocatib for Insmed, Inc, a member of the
scientific advisory board for Vividion Therapeutics, Inc., and a
consultant for Protalix, Inc outside the submitted work. T.
Merghoub is a co-founder and holds equity in IMVAQ Thera-
peutics. He is a consultant of Immunos Therapeutics, Immuno-
Genesis, and Pfizer. In addition, T Merghoub has research
support from Bristol-Myers Squibb, Surface Oncology, Kyn
Therapeutics, Infinity Pharmaceuticals Inc., Peregrine Pharma-
ceuticals Inc., Adaptive Biotechnologies, Leap Therapeutics Inc.,
and Aprea. He has patents on applications related to work on
oncolytic viral therapy, α-virus-based vaccine, neo antigen
modeling, CD40, GITR, OX40, PD-1, and CTLA-4. No other dis-
closures were reported.
Submitted: 23 December 2021
Revised: 11 March 2022
Accepted: 23 March 2022
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